One of the standard optimization strategies in computer science is genetic algorithms. These emulate organic evolution by using mutation and selection to identify the solutions of optimization problems.

Memetic algorithms are similar - but in addition to mutation and selection, they make use of individual learning, social learning and teaching. As Moscato (1989) put it:

While genetic algorithms have been inspired in trying to emulate biological evolution. Memetic algorithms would try to mimic cultural evolution.

Memetic algorithms were inspired by the observation that cultural evolution appears to have dramatically increased the rate of evolution of human civilization. If memevolution is, in some sense, faster than genevolution, maybe we can harness the power of memevolution to solve optimisation problems.

Direct thought transfer

Evolution took billions of years to produce creatures sophisticated enough to produce an open-ended type of cultural evolution based on behavioural imitation. This is because observing the actions of another and then recreating them is not a trivial task. Detailed imitation of behaviour is technically quite a difficult reverse-engineering task, which requires complex cognition to perform.

Do we have to wait until we have human-level machine intelligence before memetic algorithms can make useful contributions? No. we can engineer virtual environments in which even the relatively dumb artificial agents that we can build today can enjoy the benefits of cultural transmission. This effectively bypasses the whole problem.

Rather than passing on cultural information by clumsy processes based on behavioural imitation, memetic algorithms can work with creatures which have been designed for direct thought transfer. This can take a variety of forms. One possibility is the ability to directly pass on experiences. We can imagine the creatures have a recording device, and a device to replay the recordings to other creatures. This would be broadly similar to how humans can help each other to learn by sharing audio-visual experiences with video cameras. Other possibilities include knowledge and skill transfer. If the virtual creatures can be persuaded to represent their knowledge and skills in a portable format, this information can be transmitted directly from one creature to the next.

Collective intelligence

Groups of virtual agents being involved can potentially result in the effects associated with collective intelligence. Group-related dynamics are possible in more traditional genetic algorithms too - but social learning forces the creatures together, encouraging cooperation, and hopefully resulting in group dynamics that facilitate solving collective action problems.

Cooperation

Genetic algorithms are normally considered to be a type of competitive process - but one of the aims of memetic algorithms is to harness the power of cooperation. Letting the creatures to learn from each other encourages them to form social groups, and to work together.

Coevolution

Memetic algorithms may include a genetic component - and thus may exhibit meme-gene coevolution. Not DNA genes - of course - but rather the same kinds of genes that are involved with genetic algorithms. In cases where both memes and genes are involved, there needs to be a tradeoff made between the resources expended on each type of evolution. Managing this trade-off is a non-trivial problem.

Hybrid systems

Of course, machines don't need to have their own virtual world to be able to participate in cultural evolution. They can participate directly - by coevolving with humans on the internet. This is sometimes known as the man-machine symbiosis. It produces a kind of "impure" memetic algorithm - in which the components involved are a messy mixture of organic and machine elements. Of course such "messy memetic algorithms" are currently of great importance. This is partly because the humans and the machines can usefully compensate for each others' weaknesses. However in the future, it seems likely that we will increasingly see more machine dominated spaces - in which humans are too slow and stupid to be able to usefully contribute. Ultimately, it seems likely that we will see a memetic takeover.

Cultural algorithms

Cultural algorithms appear to be a subsequent reinvention of memetic algorithms by different researchers. The names appear to be close synonyms and the subject area appears to be the same. As far as I can tell, these were independent inventions.

Success story

Memetic algorithms has been one of the success stories of memetics in academia. There have been a long series of books, conferences and papers on memetic algorithms and memetic computing. Geeks tend to be meme-friendly, I have noticed.

Machine intelligence

Memetic algorithms lie directly on the path which leads towards machine intelligence. Cultural evolution in humans represents the process machines will need to master if they are to make very much progress. Machines are masters of mind-to-mind thought transfer, which makes it easy for them to engage in social learning. If you have a partly-intelligent machine, one obvious thing you can do to boost its power is to network it together with other similar machines - and let them cooperate with each other. The dense environment provided by modern data centers provides an ideal environment for machines to engage in social activity with each other.

Overall, it seems highly likely that memetic algorithms will play a key role in the development of machine intelligence. Memetic algorithms will thus probably prove to be the most important application of memetics - in the long term.

Sunday, 19 May 2013

The Things We Do - Using the Lessons of Bernard and Darwin to Understand the What, How, and Why of Our Behavior by Gary Cziko

Cziko wrote this book in the year 2000 - after writing Without Miracles.

It contains a history of evolution, a history of cybernetics and perceptual control theory, and section on applying these ideas to human behaviour.

Darwin will be familiar to most, but not everyone will have heard of Claude Bernard. Bernard was a french physiologist who lived at about the same time as Darwin. He studied how organisms act to control their internal environment. Cziko traces ideas about goal-directed systems through Bernard and the pioneers of cybernetics to William Powers, and perceptual control theory.

The main point seems to be that the standard, input/output model of information flow through organisms - which has perceptions leading to processing and processing leading to action - is a "linear" model which misses out something very important - namely the idea of control of perception. Feedback via the environment from action to perception is actually very important. By contrast, in perceptual control theory, organisms act so as to control their own perceptions.

The book is a good one. Most of the material about Darwinism and univeral selectionism is expressed in more detail in Without Miracles. However, this book has more historical perspective, more philosophy, and a lot more cybernetics and perceptual control theory.

The book is a little bit on the dry and boring side. However, one section that was more interesting than most was a chapter where Cziko shows how other thinkers stack up in their understanding of the subject. He rates Chomsky, Piaget, Skinner, Pinker and Dennett on their understanding of the topics in his book, giving them marks out of three. To summarize, he gives Chomsky zero, Piaget and Skinner, a half point, Pinker gets one full point and Dennett gets two and a half points. I would have given Skinner and probably Dennett more points, but otherwise, this seems about right. While this chapter seems a bit like Cziko showing off, he has a reasonable point - which is that this important material is much neglected by other thinkers.

While it's hard to argue with the significance of Darwin, Cziko makes a weaker case for the significance of Bernard. I didn't think the ideas from perceptual control theory, cybernetics and feedback were in as opposition to the conventional perception -> processing -> action models as Cziko implies. However, even if this material is less revolutionary than Cziko suggests, these are still interesting and important subject areas.

While this is a nice book, those interested in Cziko's ideas should definitely read Without Miracles first.

Saturday, 18 May 2013

Evolutionary theory was developed in the 1800s, starting with the publications of Wallace and Darwin in the 1850s.

However, it wasn't until the 1970s that people started to understand cultural evolution. It wasn't until the 1980s that books were published on the topic. It wasn't until the 21st century that the idea became widely-accepted. Now we have conferences, journals, books, papers - and a fair amount of activity. Understanding of organic evolution preceded understanding of cultural evolution by over a hundred years. I've written before about this scientific lag.

Genetics came later. The rediscovery of Mendel's ideas didn't happen until around 1900. Population genetics and the modern evolutionary synthesis didn't happen until the 1930s. Molecular genetics had to wait until the 1950s before the basics of the field were understood.

That brings us to memetics. Memetics stands to cultural evolution as genetics stands to organic evolution. It looks as though there are some parallels with the organic realm regarding the chronology of its development. Understanding of memetics shows signs of lagging behind an understanding of cultural evolution. Also, population memetics was developed before neuromemetics.

There are some areas where memetics is more advanced than genetics. Memetic engineering is probably more advanced than genetic engineering. However, that is probably not down to a more advanced scientific understanding of the topic. Rather memes, by nature, are easier to read, write, understand and engineer than genes are.

Looking at the memetics timeline and the field's publication record, in terms of a widespread understanding of memetics, we are fairly clearly still before the cultural equivalent of the modern synthesis of the 1940s, and before the cultural equivalent of the molecular genetics revolution of the 1950s. So: it seems fairly clear that the memetics pioneers are ahead of their time.

On one hand, that makes these exciting times for the field. On the other hand, it means that we have to wait for the rest of the scientific community to catch up.

Friday, 17 May 2013

Just as population genetics is the study of how gene frequencies change in populations, so population memetics is the study of meme frequencies change in populations.

The basis for both fields is frequency analysis - a subject historically associated with cryptanalysis, but more generally a branch of statistics. frequency analysis can be applied to genes, memes, and practically anything else which can be divided into discrete categories for analysis. Much of population memetics consists of data gathering followed by meme frequency analysis.

Population memetics is one of the most studied areas of memetics. It's relatively trivial to measure cultural traits and see how they change and spread through populations over time. Most of the approaches to cultural evolution in academia have been based on ideas derived from population genetics.

Population memetics is involved in harvesting the raw data needed to test most theories in cultural evolution and memetics. Harvesting techniques include questionnaires, and direct observation of behaviour and artifacts - both in the field and in laboratories.

The failure of social evolutionists to properly apply a fully Darwinian model to culture until fairly recently is in part due to the prior expectations everybody has about what cultural agents are, and partly also to popular misunderstandings about Darwinian evolution; including, it has to be said, by many biologists. It is not through lack of intelligence, but through the complexity and sometimes vagueness of presentations of Darwinism that this occurs, for ‘Darwinism’ is itself an evolving tradition, as all scientific theories are in the end (Hull, 1988b).

Our minds, it seems, are not well equipped to understand how they themselves work. You, in fact, may at first be very confused or distracted, or suddenly get tired, as you read this; you may even become angry just from reading these words. Although right now you may think that this statement is absurd, those feelings and symptoms are actually the defense mechanisms of mind viruses. They have evolved to be very protective of the parts of your mind that they’ve stolen, and any attempts to cleanse yourself of them can trigger reactions.

The ultimate meme trick: Why your memes want you to hate the idea of memes

Stanovich argues that our memes don't "want" us to understand that a host can be taken over by ideas that treat their host as a tool for their own propagation. Stanovich argues that - if this is a common defense mechanism of multiple memeplexes, this effect might possibly lead to the observed memetics resistance.

These ideas from Brodie and Stanovich are stimulating - if rather difficult to test. Humans might also appear to be genetically predisposed to have a high opinion of themselves - and so might be naturally-resistant to seeing themselves as having parasite-ridden brains. If so, memeplexes seeking to amplify such sentiments may have had some existing material to work with.

Saturday, 11 May 2013

I've written a good deal about evolutionary progress. That evolution is not progressive is a matter of faith for most in the field these days. This idea is basically a mistake. Kevin Kelly offers one of the clearest explanations of why it is a mistake in his book What Technology Wants. Because his exposition is comprehensive and clear, those in doubt should read his treatment.

Stephen Gould long ago persuasively argued that there is no necessary direction of increased complexity throughout evolution. The only reason why complexity historically follows simplicity is because life had to start simple, so it only had “more complex” as a direction of (stochastic, not directed) movement. It’s a so-called “left wall” effect: if you start walking (randomly, even) from near a wall, the place you end up is away from the wall.

This "left wall effect" makes a good null hypothesis. However, it's just wrong as a model of real world evolution. Evolution isn't just drift - there's also selection!

I think cultural evolution makes the issue of evolutionary progress clearer. It takes a dyed-in-the-wool post-modernist to argue that cultural evolution is not progressive. Practically everyone agrees that cultural evolution exhibits progress. A curious exception is Alex Mesoudi - who argued against all kinds of evolutionary progress in his recent book on cultural evolution.

I think that progress denialism is unscientific nonsense. It arose as a reaction against unilinear theories of social Darwinism. To me, it seems like a form of political correctness gone mad.

Universal computation describes systems in terms of their relationship to abstract computing devices which are capable of computing anything that can be computed.

Universal Darwinism characterizes systems in terms of how they change over time - and divides their dynamics into copying, selection and variation.

This post will consider how these ideas are related. In particular, it will consider computation in the light of Darwinism.

There are various models of universal computers, but they all have equivalent capabilities. One way of making a universal computer involves interconnect and NAND gates. NAND gates have the property known as functional completeness - which means that they can be connected together to emulate any other logic gate or computational system. The truth table for a NAND gate looks like this:

Branching interconnect results in signals being copied - from the "input" branch to all the "output" branches. The NAND gate itself results in selective data transmission. You can see this by considering that when A is 0, the signal from B is destroyed[1], while when A is 1 the signal from B is transmitted through. It is true that the signal from B is inverted - but that's an information-theorynull-op: if you want the original signal back, you can just invert it again.

So: computers exhibit copying and selection ubiquitously - what about variation? Variation arises inside computers to. Variation is just copying that is inaccurate or incomplete - and of course, this happens all the time.

This characterization of computation in Darwinian terms is helpful - since it allows the large body of theory descended from Darwin's work to be applied to computers and computer networks. Indeed, according to the computability thesis, any physical system can be emulated by a universal computer - so the domain of these theories includes all physical systems.

[1] What about reversible computers? Selection doesn't depend on the destruction of information. It is enough for the information to go into a trash basket somewhere. So, the same argument can be applied to Fredkin gates.

Friday, 10 May 2013

I wrote about the history of cultural evolution in my 2011 book. Later parts of that material was expanded into the Memetics Timeline. However, the story as I told it is rather abbreviated. There have been various review articles and book paragraphs that have given an overview of the history of the field - e.g. Laland and Brown (2004) and Blackmore (1999) - but the field is still lacking a substantial history.

There's now a long trail of academic papers and books on the topic. We have biographies of some of the players - e.g. Dennett, Dawkins, Skinner, Darwin and Price. Someone should put all the pieces together and write a history of the field.

It's true that the field is still in flux - but it might stay that way for a while. Scientific historians should not be too deterred by history still being in the making.

Though I produced the Memetics Timeline, I should say that scientific history isn't really my area. I don't plan to write the history of the field in much more detail than I already have. I think that it is time for someone else to have a go at the topic.

Update 2015-05-10: Brent Jesiek's 110 page MSc thesis presents a comprehensive history of memetics. It mostly concentrates on the period from 1975 to 2003. It is available free of charge online - to ResearchGate members.

Sunday, 5 May 2013

This book argues that Adam Smith's idea of an invisible hand in economics is a metaphor with some significant limitations - and that a Darwinian perspective shows how individual self-interest and group benefit are often in conflict and that individual selfishness often leads to bad outcomes at higher levels.

Frank's examples of unhealthy individual self-interest in biology include products of runaway sexual selection. He lists a number of examples - such as peacock's tails and oversize antlers. He compares these with similar wasteful processes in economics - such as "conspicuous consumption" and other forms of status displays. Frank says that a Darwinian perspective predicts and explains such cases - while the idea of an "invisible hand" does not.

These ideas are good, but they are only a small part of the book. Most of the book argues for making some economic changes, in the light of a Darwinian perspective.

The main proposed changes seem to be changes to taxation. Frank promotes the idea of sin taxes. He proposes we tax total consumption directly - rather than directly taxing sales - and suggests a sliding scale where the rich get taxed more. He proposes taxing heavy vehicles, tobacco and alcohol, and emissions of carbon dioxide sulphur dioxide.

He pictures his main opponents as libertarians, who oppose most taxation. A substantial fraction of the book involves pointing out how crazy the libertarian positions are. I tired of this material rather quickly - since Frank was preaching to the converted in my case - I can't take libertarian positions seriously.

The book is generally great. However, Frank spends a lot of time on his libertarian critics - and not enough time on other more interesting criticisms.

Frank seems to generally favour more taxes - but he doesn't spend much time addressing the question of how much taxation is the right amount. Cries for more taxation should try to address this question.

Frank realizes that countries with higher taxes will be unattractive places to run businesses. His argument about why this is not a problem invokes the idea that countries with less taxes are not such nice places to live. This idea appears to be nonsense to me. I spent much of my life in England, which has a few nearby tax havens - in the form of Ireland and the channel islands: Jersey and Guernsey. Jersey and Guernsey in particular have a great climate, are full of rich people and are miniature paradises. Businesses based there have pretty good access to English consumers. Most people don't live there - simply because they can't afford the land prices. In such cases, Frank's argument about tax havens being places where people don't want to live seems to fall on its nose.

Lots of taxation tends to produce black markets which fund criminal undergrounds. Sin taxes can only be taken so far because this sort of effect starts to kick in after a while.

Similarly Frank doesn't spend much time on tax evasion. Some taxes are easier to avoid than others - and tax evasion is pretty big business. Levels of taxation on undesirable actions have to be set in the light of the ease of tax evasion. Fortunately, conspicuous consumption is often easy to tax - since it is by nature easily visible.

Frank's plans mostly seem to revolve around taxing activities that are currently not taxed very much. However there's also scope for raising funds via taxing actions that are currently illegal - such as consuming some drugs and prostitution. Such a discussion might have added some spice and could have replaced some of the book's more repetitive elements - but this topic was not covered.

Lastly, Frank is basically proposing a tax plan that benefits the poor, at the expense of the rich. It is true that many people might vote for such a tax plan, but it is also true that other people might use lobbying, campaign donations and so forth to oppose it. Politics, proverbially, is the fine art of getting money from the rich and votes from the poor while promising each that you will protect them from the other. Frank's proposed policies might get votes from the poor, but they probably won't attract much money from the rich. This makes them less likely to be implemented.

Despite spending his energy on some of the the sillier criticisms of his ideas, many of Frank's proposals seem sensible. Consumption taxes are generally favoured by most economists, and a sliding scale that taxes the rich more makes obvious sense - compared to sales taxes. Sin taxes are fairly common anyway - the main issue is where they can be best applied.

In summary, this is a pretty good book, which should be read by anyone with an interest in how biological ideas apply to economic issues.